scholarly journals Abstract-concept learning carryover effects from the initial training set in pigeons (Columba livia).

2009 ◽  
Vol 123 (1) ◽  
pp. 79-89 ◽  
Author(s):  
Tamo Nakamura ◽  
Anthony A. Wright ◽  
Jeffrey S. Katz ◽  
Kent D. Bodily ◽  
Bradley R. Sturz
Keyword(s):  
Concept Learning ◽  
Columba Livia ◽  
Abstract Concept ◽  
Initial Training ◽  
Training Set ◽  
Carryover Effects

Abstract Concept Learning in Magpies (Pica pica)

2014 ◽  
Author(s):  
John Magnotti ◽  
Jeffrey Katz ◽  
Anthony Wright ◽  
Debbie Kelly
Keyword(s):  
Concept Learning ◽  
Abstract Concept ◽  
Pica Pica

Effects of Set-Size on Abstract Concept Learning in Rats Using Olfactory (N)MTS Procedures

2010 ◽  
Author(s):  
Lucia Lazarowski ◽  
Rachel Eure ◽  
Mallory Gleason ◽  
Adam Goodman ◽  
Aly Mack ◽  
...  
Keyword(s):  
Concept Learning ◽  
Abstract Concept ◽  
Set Size

Abstract concept learning in black-capped chickadees

2011 ◽  
Author(s):  
Marisa Hoeschele ◽  
Robert G. Cook ◽  
Lauren M. Guillette ◽  
Allison H. Hahn ◽  
Christopher B. Sturdy
Keyword(s):  
Concept Learning ◽  
Abstract Concept

Oddity-from-Sample Abstract-Concept Learning by Pigeons

2011 ◽  
Author(s):  
Thomas A. Daniel ◽  
Jeffrey S. Katz ◽  
Anthony A. Wright
Keyword(s):  
Concept Learning ◽  
Abstract Concept

Abstract-concept learning differs when vertical and horizontal stimulus panels are used in MTS by pigeons

2003 ◽  
Author(s):  
Jeffrey S. Katz ◽  
Kent D. Bodily ◽  
Michelle Hernandez ◽  
Anthony A. Wright
Keyword(s):  
Concept Learning ◽  
Abstract Concept

Abstract-concept learning and list-memory processing

2003 ◽  
Author(s):  
Anthony A. Wright ◽  
Jeffrey S. Katz ◽  
Jacquelyne J. Rivera ◽  
Jocelyne Bachevalier
Keyword(s):  
Concept Learning ◽  
Abstract Concept ◽  
Memory Processing ◽  
List Memory

scholarly journals Abstract concept learning in a simple neural network inspired by the insect brain

2018 ◽  
Vol 14 (9) ◽  
pp. e1006435 ◽  
Author(s):  
Alex J. Cope ◽  
Eleni Vasilaki ◽  
Dorian Minors ◽  
Chelsea Sabo ◽  
James A. R. Marshall ◽  
...  
Keyword(s):  
Neural Network ◽  
Concept Learning ◽  
Insect Brain ◽  
Abstract Concept ◽  
Simple Neural Network

Coupling Sentiment Dictionary and SVM Classification for Text Orientation Analysis

2014 ◽  
Vol 989-994 ◽  
pp. 2444-2449
Author(s):  
Ming Ze Gao ◽  
Fang Fang Li ◽  
Zhe Yuan Ding ◽  
Wei Dong Xiao
Keyword(s):  
Classification Accuracy ◽  
Opinion Mining ◽  
Svm Classifier ◽  
Classification Methods ◽  
Initial Training ◽  
Training Set ◽  
Orientation Analysis ◽  
Second Stage ◽  
Sentiment Dictionary ◽  
Two Stages

Sentiment classification finds various applications in opinion mining, which can help users determine sentiment tendency of texts and information. In this paper, we consider the problem of text orientation analysis. In particular, we propose a two-stage approach by coupling sentiment dictionary and classification methods. In the first stage, we build sentiment dictionary and rules to obtain the texts whose emotional scores are ranked in the top 1/4 and the bottom 1/4. These texts are marked classified for supervising the second stage. In the second stage, we employ the SVM classifier to process the remaining texts. Finally, we combine the two stages to get the orientation analysis results for all the texts. Experimental results demonstrate that, in contrast to using sentiment dictionary and classification method separately, our proposed method achieves higher classification accuracy when an initial training set by manual tagging is unavailable.

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